@Wikipedia: #notability versus #relevance

I had a good discussion with imho a deletionist Wikipedia admin. For me the biggest take away was how notability is in the way of relevance.

With statements made like: "There are only two options, one is that the same standards apply, and the other is the perpetuation of prejudice" and "I view our decisions of notability as primarily subjective--decisions based on individual values and understandings of what WP should be like" no/little room is given for contrary points of view.

Notability has as its problem that it enables such a personal POV while relevance is about what others want to read. For a professor Bart O. Roep there is no article. Given two relevant diabetes related awards he should be notable and as he started a human study for a vaccine for diabetes type 1, he should be extremely relevant.

A personal POV ignoring the science that is in the news has its dangers. It is easy enough for Wikimedians to learn about scientific credentials, the papers are there to read but what we write is not for us but for our public. Withholding articles opens our public up to fake facts and fake science. An article about Mr Roep is therefore relevant and timely particularly because people die as they cannot afford their insulin. Articles about the best of what science has to bring about diabetes now is of extreme relevance.

At Wikidata, there is no notability issue. Given the relevance of diabetes all that is needed is to concentrate effort for a few days on a subject. New authors and papers are connected to what we already have, genders are added to authors (to document the gender ratio) and as a result more objective facts available for the subjective Wikipedia admins to consider, particularly when they accept tooling like Scholia to open up the available data.
Thanks,
      GerardM

#Wikidata - Exposing #Diabetes #Research

People die of diabetes when they cannot afford their insulin. There is not much that I can do about it but I can work in Wikidata on the scholars, the awards, the papers that are published that have to do with diabetes. The Wikidata tools that are important in this are: Reasonator, Scholia and SourceMD and the ORCiD, Google Scholar and VIAF websites prove themselves to be essential as well.

One way to stay focused is by concentrating on awards and, at this time it is the Minkowski Prize, it is conferred by the European Association for the Study of Diabetes. The list of award winners was already complete so I concentrated on their papers and co-authors. The first thing to do is to check if there is an ORCiD identifier and if that ORCiD identifier is already known in Wikidata, I found that it often is and merges of Wikidata items may follow. I then submit a SourceMD job to update that author and its co-authors.

The next (manual) step is about gender ratios. Scholia includes a graphic representation of co-authors and for all the "white" ones no gender has been entered. The process is as follows: when the gender is "obvious", it is just added. For an "Andrea" you look them up in Google and add what you think you see. When a name is given as "A. Winkowsky", you check ORCiD for a full name and iterate the process.

Once the SourceMD job is done, chances are that you have to start the gender process again because of new co-authors. Thomas Yates is a good example of a new co-author, already with a sizable amount of papers (95) to his name but not complete (417). Thomas is a "male".

What I achieve is an increasingly rich coverage of everything related to diabetes. The checks and balances ensure a high quality. And as more data is included in Wikidata, people who query will gain a better result.

What I personally do NOT do is add authors without an ORCiD identifier. It takes much more effort and chances of getting it wrong make it unattractive as well. In addition, I care for science but when people are not "Open" about their work I am quite happy for their colleagues to get the recognition they deserve.
Thanks,
      GerardM